There are new imaging modalities emerging which provide not just a single image of the patient or the object, but two or more of them in exactly the same geometry. Two examples for this are differential phase contrast imaging (DPCI; e.g. described in US 2012/0099702 A1), where the real and imaginary part of the complex refractive index are measured, and spectral CT (e.g. described in US 2008/0253504 A), where the x-ray attenuation due to the photoelectric effect, Compton scattering, and possibly due to contrast agents are recovered.
In WO 2011/145040 A1 joint bilateral filtering has been proposed as a generalization of the well-known bilateral filter for image based de-noising. In particular, an image processing apparatus is described comprising an image providing unit for providing a first image of an object and a second image of the same object and a filtering unit which filters the first image depending on a first degree of similarity between image values of the first image and on a second degree of similarity between image values of the second image. This allows filtering the first image depending on the likeliness that image values belong to the same part of the object, for example, to tissue or to bone material of the object, if the object is a human being or an animal, even if due to noise the image values of one of the first image and the second image are disturbed, thereby improving, for example, an edge preserving image based-denoising of CT images.
The known methods and devices do, however, not acknowledge that noise in the various images can be correlated. In particular, for DPCI there is a strong spatial correlation in transaxial images of noise within the phase contrast image (which is equivalent to the well known noise power spectrum that has peak at low frequencies), and for spectral CT there is a strong anti-correlation of noise at the same spatial location in the photo- and the Compton-image.
There may be also other situations where two images of the same object are available, but at different spatial resolution, which is also reflected by different spatial correlation in the noise. An example may be a magnetic resonance imaging (MRI), where in some situations an anatomical (e.g., T2 weighted) and a parametric image (T1) is acquired.